Supervised machine learning algorithms for predicting student dropout and academic success: a comparative study
Abstract Utilizing a dataset sourced from a higher education institution, this study aims to assess the efficacy of diverse machine learning algorithms in predicting student dropout and academic success. Our focus was on algorithms capable of effectively handling imbalanced data. To tackle class imb...
| Principais autores: | , |
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| Formato: | Artigo |
| Idioma: | English |
| Publicado em: |
Springer
2024-01-01
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| coleção: | Discover Artificial Intelligence |
| Assuntos: | |
| Acesso em linha: | https://doi.org/10.1007/s44163-023-00079-z |